Automatic fingerprint center point determination by using modified directional field and morphology

T. B.J. Andrew; T. S. Ong; N. C.L. David; Y. W. Sek

doi:10.1007/978-3-540-24581-0_54

Automatic fingerprint center point determination by using modified directional field and morphology

T. B.J. Andrew, T. S. Ong, N. C.L. David, Y. W. Sek

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

Accurate and reliable center point determination of the fingerprint is an essential pre-processing step for the image based fingerprint recognition approach. This step is particularly important since a reference point is required to cancel the variation in position of the reference and testing fingerprint image. This paper illustrated an automatic center point determination algorithm that couples the modified averaged square directional field (MASDF) with morphological operation, in order to pinpoint the center point of the fingerprint efficiently and accurately. The experiment result shows only 3.13% rejection rate for the false center point by using the proposed method.

Original language	English
Title of host publication	AI 2003
Subtitle of host publication	Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings
Editors	Tamas D. Gedeon, Lance Chun Che Fung, Tamas D. Gedeon
Publisher	Springer Verlag
Pages	633-640
Number of pages	8
ISBN (Print)	9783540206460
DOIs	https://doi.org/10.1007/978-3-540-24581-0_54
Publication status	Published - 2003
Event	16th Australian Conference on Artificial Intelligence, AI 2003 - Perth, Australia Duration: 2003 Dec 3 → 2003 Dec 5

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2903
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	16th Australian Conference on Artificial Intelligence, AI 2003
Country/Territory	Australia
City	Perth
Period	03/12/3 → 03/12/5

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2003.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-24581-0_54

Cite this

Andrew, T. B. J., Ong, T. S., David, N. C. L., & Sek, Y. W. (2003). Automatic fingerprint center point determination by using modified directional field and morphology. In T. D. Gedeon, L. C. C. Fung, & T. D. Gedeon (Eds.), AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings (pp. 633-640). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2903). Springer Verlag. https://doi.org/10.1007/978-3-540-24581-0_54

Andrew, T. B.J. ; Ong, T. S. ; David, N. C.L. et al. / Automatic fingerprint center point determination by using modified directional field and morphology. AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. editor / Tamas D. Gedeon ; Lance Chun Che Fung ; Tamas D. Gedeon. Springer Verlag, 2003. pp. 633-640 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Accurate and reliable center point determination of the fingerprint is an essential pre-processing step for the image based fingerprint recognition approach. This step is particularly important since a reference point is required to cancel the variation in position of the reference and testing fingerprint image. This paper illustrated an automatic center point determination algorithm that couples the modified averaged square directional field (MASDF) with morphological operation, in order to pinpoint the center point of the fingerprint efficiently and accurately. The experiment result shows only 3.13% rejection rate for the false center point by using the proposed method.",

author = "Andrew, {T. B.J.} and Ong, {T. S.} and David, {N. C.L.} and Sek, {Y. W.}",

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Andrew, TBJ, Ong, TS, David, NCL & Sek, YW 2003, Automatic fingerprint center point determination by using modified directional field and morphology. in TD Gedeon, LCC Fung & TD Gedeon (eds), AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2903, Springer Verlag, pp. 633-640, 16th Australian Conference on Artificial Intelligence, AI 2003, Perth, Australia, 03/12/3. https://doi.org/10.1007/978-3-540-24581-0_54

Automatic fingerprint center point determination by using modified directional field and morphology. / Andrew, T. B.J.; Ong, T. S.; David, N. C.L. et al.
AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. ed. / Tamas D. Gedeon; Lance Chun Che Fung; Tamas D. Gedeon. Springer Verlag, 2003. p. 633-640 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2903).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Andrew, T. B.J.

AU - Ong, T. S.

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N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2003.

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N2 - Accurate and reliable center point determination of the fingerprint is an essential pre-processing step for the image based fingerprint recognition approach. This step is particularly important since a reference point is required to cancel the variation in position of the reference and testing fingerprint image. This paper illustrated an automatic center point determination algorithm that couples the modified averaged square directional field (MASDF) with morphological operation, in order to pinpoint the center point of the fingerprint efficiently and accurately. The experiment result shows only 3.13% rejection rate for the false center point by using the proposed method.

AB - Accurate and reliable center point determination of the fingerprint is an essential pre-processing step for the image based fingerprint recognition approach. This step is particularly important since a reference point is required to cancel the variation in position of the reference and testing fingerprint image. This paper illustrated an automatic center point determination algorithm that couples the modified averaged square directional field (MASDF) with morphological operation, in order to pinpoint the center point of the fingerprint efficiently and accurately. The experiment result shows only 3.13% rejection rate for the false center point by using the proposed method.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - AI 2003

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T2 - 16th Australian Conference on Artificial Intelligence, AI 2003

Y2 - 3 December 2003 through 5 December 2003

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Andrew TBJ, Ong TS, David NCL, Sek YW. Automatic fingerprint center point determination by using modified directional field and morphology. In Gedeon TD, Fung LCC, Gedeon TD, editors, AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. Springer Verlag. 2003. p. 633-640. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-24581-0_54

Automatic fingerprint center point determination by using modified directional field and morphology

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